\section{The Final Thoughts -- what we have learned}
\label{sec:answers}

In this section we want to discuss our findings and the justification of eventual grounded theory. And so this is a kind of wrap-up summary of the most important points of this research which will include an evaluation of our theoretical and methodological approach. This will lead to a discussion regarding the extent to which we have answered to our research question. We will point to future research that can validate our findings and grounded theory and this will also function as an evaluation of the whole research project.

\subsection{Grounded theory}

We started out with the initial presumptions (1) that open data has a democratizing effect that can increase social capital and by that allows collective decision-making and holistic smart city solutions that enable sustainable development, and (2) that open public and private data can lead to cross-sector innovation and function an enabler of other smart city innovations/solutions. That lead to the formulation of the main research question of how a conceptual maturity model for assessing and guiding open data collaboration. We also committed ourselves to investigate the sustainability enabling effects of open data collaboration and the most important incentive structures for participating in such a collaboration. This was the point of departure of our grounded theory approach. \bigskip

\noindent By means of a structured empirical approach we collected data that gradually shaped our knowledge and it was condensed and held up against the theory presented in chapter \ref{chap:theory}. That led to grounded theories that is well founded in theory and the scope of practice that we included in this research. It is our assumption that our primary data represent a significance of the prevailing perceptions of the subject matter. \bigskip

\noindent First of all we have depicted that open data maturity can be put into five different categories (figure \ref{tab:maturityperspectives}). Such a categorization can function as a useful taxonomy when dealing with maturity in a complex system such as a city. We have found it useful to in the development and communication of a normative maturity model.

Furthermore, we have shown that sustainability in a smart city context is not only about addressing environmental issues -- the concept easily becomes a cliché if it is not carefully treated. The concept of sustainable development \citep{HILTY} inherently requires balancing the social, economic, and environmental issues and it is the primary task of a smart city to strive for it. We have shown that sustainable development cannot be achieved on a city level without a certain amount of collective maturity among relevant actors so they understand the need for holistic thinking and business silos breakdown that can lead to synergy creation and system agility. Sufficient incentives for actors to break down their business silos can only be created if the complexity of the city is broken down to tangible subsystems/projects where concrete short-term wins can be formulated and the initial purpose of the project is easy to understand. Therefore we argue that 

\begin{description}
\item[Theorem 1:] \textit{Sustainability (economic, environmental, and social) and sustainable development must be fostered from a bottom-up approach in a complex system such as a city.}
\end{description}

\noindent Sustainability is not a goal in itself but covers the ability of the system actors to take collective action towards an ideal optimum. Our research depicts the inevitable wicked problems in a society: what might be beneficial for one actors might harm other actors; what might be beneficial for the environment might harm business opportunities and welfare. Sustainability is a concept that has to be aligned across all system actors to minimize these rebound effects. Our research shows that the only way to do that is to break down the complex system into subsystems around concrete projects; here sustainability can be automatically fostered because a holistic mindset can be developed and incentives can be created for breaking down business silos. We have showed that open data is a means to achieve this bottom-up sustainability.

Therefore we can define a smart city as below:

\begin{description}
\item[Theorem 2:] \textit{A smart city is a complex purposive system consisting of ideal-seeking subsystems that are in a continuous process of evolving and integrating with other subsystems and in which actors are in a continuous process of breaking down business silos.}
\end{description}

\noindent The result of our research is a normative model for achieving this kind of smart city and the concept of open data is a means to collectively break down business silos and enable sustainability by making rebound effects quantifiable. At the same time open data is a tool for sustainability enabling smart city solutions because it allows actors to share information and create synergies that inherently balance all the areas of sustainability.

\subsection{Answers to our research question}

Let us recall the exact formulation of our research question and subques\-tions: \bigskip
\begin{quote}
\noindent How can we make a conceptual maturity model for assessing open data maturity of a smart city ecosystem, which normatively can function as a guideline for relevant actors?


\begin{description}

\item[\textit{Subquestion 1:}] How can open data be used as a sustainability-enabler in the context of smart cities?

\item[\textit{Subquestion 2:}] What are the most important incentive structures for attracting support for such a model among smart city actors?

\end{description}
\end{quote}

\noindent The primary answer to our main research question is that we have been able to make such a model by means of using a grounded theory methodology that allowed us to combine our prior knowledge with secondary theoretical data and primary empirical data. This has revealed that there are many different categories of open data maturity and a matrix model can work as an assessment tool and provide normative guidelines for collective action. The process has enabled us to create a conceptual maturity model, which we want to call the Open Governance Maturity Matrix because it reflects that a successful open data approach to a smart city initiative is only reached in an open governance environment.

Our maturity matrix can assess the maturity stage of a smart city project that is based on open data. At the same time it provides normative guidelines towards increasing the maturity of the project. Therefore we argue that we have successfully have answered our main research question. The maturity matrix is verified through the usage of a grounded theory methodology, but it is not validated and therefore it can only be considered conceptual. In other words: we have used a \textit{valid} methodology to build the maturity model, and so we know that we have \textit{built the model right}. We have not ensured that we have \textit{built the right model}. We have some ideas for the validation of the model which will be presented in the coming subsection \ref{subsec:futureideas}. \bigskip

\noindent Regarding subquestion 1, we have induced that if open data is used to break down business silos and to create cross-silo synergies it can function as a sustainability enabler. Sustainability is reached if smart city initiatives initiate in concrete ideal-seeking subsystems where collective open data maturity can be quantified and increased. Open data can be used to enable sustainability (1) directly by exploiting existing resources more efficiently by sharing them and (2) indirectly by using it as a means to increase the maturity of actors' collective mindsets and aligning visions that balance economic, social, and environmental sustainability and by that minimize eventual rebound effects. \bigskip

\noindent Incentive structures have to be in place for attracting actors to participate in such a collective action. We have found that the most important incentives for participation is that actors can formulate their own requirements for short-term wins that can be built in to the project from the beginning. Short-term wins are necessary for reaching long-term goals. Another important incentive for participation is to proper understanding what open data is and its potential value. Therefore structures for these types of incentivisation have to be built into a normative model like ours.

During the maturing process more incentives for participation and collaboration will emerge as business silos are gradually broken down and valuable cross-silo synergies appear. Thereby we have also answered subquestion 2. 

\subsection{Ideas for future research}
\label{subsec:futureideas}

As previously mentioned, we have not tested and validated the Open Governance Maturity Matrix as part of this research. We will now discuss how such a validation process can look like in the future. Furthermore, we will point to future research that can make the argumentation behind the Open Governance Maturity Matrix stronger and that can lead to a more comprehensive model. \bigskip

\noindent A typical theory testing/validation process can happen through case studies based on deduction \citep{SAUNDERS,KUADA}. Such deduction studies would  have to opportunity to reveal in what kinds of contexts the Open Governance Maturity Matrix can be used and what changes are needed for it to fit to certain contexts. 

Deductive case studies can show if our maturity matrix only fits to a Danish/European context in its current form, which is likely to be the case because of our choice of interviewees and scope. Institutional design and business ecosystems construction might require other design techniques and mechanisms due to different political systems, cultures, and mindsets. And so, deductive studies will increasingly refine the maturity matrix and define its limitations and usability and by that make it more valid in certain contexts. 

An obvious place to start can be the case of Copenhagen Connecting where a study will reveal if our maturity matrix is acceptable by the steering committee and the stakeholders and if steps or questions are missing in the normative maturing process. It will reveal if the visualisation of the maturity steps and conditions are sufficient for incentive creation and as a basis for collaboration. There are indeed many parameters which can be tested to strengthen efficacy of the maturity matrix and make it more valid. \bigskip

\noindent Theorem 1 and 2 are induced from our findings and provide workable definitions of sustainability and smart cities that can contribute to the successful implementation of the Open Governance Maturity Matrix. These theorems are falsifiable in that they can be tested and refined. Reformulation of these theorems is causal to rethinking the maturity matrix and vice versa. According to \cite{POPPER} falsifiability is key to genuine theory because

\begin{quote}
\textit{``[c]onfirming evidence should not count except when it is the result of a genuine test of the theory; and this means that it can be presented as a serious but unsuccessful attempt to falsify the theory.''} \citep[p. 35]{POPPER}
\end{quote}

\noindent Therefore, future research studies can set up a predefined series of attempts to falsify the Open Governance Maturity Matrix. The results of such studies is a validation process \citep{WALLIS}. 

